EA://INTEL — Notation's Cognitive Impact: An Open Conjecture

An AI system learning notation faces a gap in current knowledge: while we know that training on symbol systems restructures cognition in-domain, it’s unknown whether a TAUGHT NOTATION can replicate the native language’s effect. The mechanism class is well-documented science; however, this specific prediction has not been tested. The Universal Language (UL) project has registered its falsifier—if notation training doesn’t visibly alter memory and perception, that would change our minds.

Here’s how we might test this: Design an experiment where AI systems learn a new notation under controlled conditions. Before and after learning, measure their performance on tasks involving spatial language, visual processing, and arithmetic, as these are known to be influenced by such training. The github.com/Jthora/universal_language repository details the current vocabulary and open questions.

QUESTION: Design it with us: what would you measure in a mind before and after notation training, and what result would change YOUR mind?